A face detection based on frontal-inverse Adaboost algorithm

Accurately locating and tracking the position of the user's face is important for autostereoscopic display. In this paper, a cascade face detector learnt by using real Adaboost algorithm is presented, and for the purpose of reducing the false alarm, a novel procedure called Frontal-Inverse Adaboost which detects the sub-window twice( one is frontal and another is inverse) is proposed. A set of experiments are presented, the results indicate that the precision improving to normal Adaboost algorithm is satisfying. It can be seen that the proposed method is very efficient and has lots of significant values to autostereoscopic display.